import numpy as np
import pandas as pd
%matplotlib inline
import seaborn as sns
import matplotlib.pyplot as plt
from ipywidgets import widgets, interact
sns.set(style="darkgrid",)
sns.set_palette('deep')
sns.set_context("talk")
filename = r'Results\CSV\PU\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_007.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0.0, 0.4)]
sns.set_context("paper")
filename = r'Results\CSV\PU\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df['Zero'] = (df['COF']<0.05)
df['T_c'] = df['T']-0.3770
df['X'] = (4.66/2)*np.cos(4*np.pi*df['T_c'])
df['V'] = (4.66/2)*4*np.pi*np.sin(4*np.pi*df['T_c'])
Vmed = 30000/df['T'].max()
ndf = df[abs(df['V'])>Vmed]
df
| Tempo (s) | Fx | Fz | Z | X | Ff | Coeficiente de atrito cinético (-) | Zero | T_c | V | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.0000 | -0.054 | -2.563 | -0.0100 | 5.855312e-02 | 0.054 | 0.021 | True | -0.3770 | 29.270397 |
| 1 | 0.0010 | -0.075 | -2.580 | -0.0100 | 2.927887e-02 | 0.075 | 0.029 | True | -0.3760 | 29.277332 |
| 2 | 0.0020 | -0.102 | -2.600 | -0.0105 | -4.280141e-16 | 0.102 | 0.039 | True | -0.3750 | 29.279644 |
| 3 | 0.0030 | -0.119 | -2.628 | -0.0105 | -2.927887e-02 | 0.119 | 0.045 | True | -0.3740 | 29.277332 |
| 4 | 0.0040 | -0.127 | -2.653 | -0.0105 | -5.855312e-02 | 0.127 | 0.048 | True | -0.3730 | 29.270397 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 1615044 | 1615.0439 | -0.727 | -2.623 | 0.0035 | -1.170912e+00 | 0.727 | 0.277 | False | 1614.6669 | 25.313880 |
| 1615045 | 1615.0450 | -0.740 | -2.649 | 0.0035 | -1.198644e+00 | 0.740 | 0.279 | False | 1614.6680 | 25.108075 |
| 1615046 | 1615.0460 | -0.744 | -2.665 | 0.0035 | -1.223657e+00 | 0.744 | 0.279 | False | 1614.6690 | 24.916815 |
| 1615047 | 1615.0470 | -0.697 | -2.618 | 0.0035 | -1.248476e+00 | 0.697 | 0.266 | False | 1614.6700 | 24.721621 |
| 1615048 | 1615.0480 | -0.667 | -2.567 | 0.0035 | -1.273099e+00 | 0.667 | 0.260 | False | 1614.6710 | 24.522522 |
1615049 rows × 10 columns
#df = df.rename(columns={'T':'Tempo (s)', 'COF':'Coeficiente de atrito cinético (-)'})
d = df[(df['Tempo (s)']>705)&(df['Tempo (s)']<706)]
sns.set(font_scale=1.5, rc={"lines.linewidth": 1})
g = sns.relplot(data = d, kind = 'line', x = 'Tempo (s)', y='Coeficiente de atrito cinético (-)')
g.set(ylim=(0, 0.37))
#df['T_r']= df['T'].round(0)
#sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x16780c57288>
filename = r'Results\CSV\PU\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1c0a0b08>
filename = r'Results\CSV\PU\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_008.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PU\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1d643308>
filename = r'Results\CSV\PU\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PU\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1d6fdd88>
filename = r'Results\CSV\PU\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_010.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PU\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1d6cc248>
filename = r'Results\CSV\PU\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PU\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1df35588>
filename = r'Results\CSV\PU\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PU\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PU\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1df0dcc8>
filename = r'Results\CSV\PU\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1d431f88>
filename = r'Results\CSV\PU\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1df73148>
filename = r'Results\CSV\PU\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1c04b2c8>
filename = r'Results\CSV\PU\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd209a9a48>
filename = r'Results\CSV\PU\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd220bd048>
filename = r'Results\CSV\PUEG1\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_007.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG1\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1a036748>
filename = r'Results\CSV\PUEG1\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_010.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG1\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1d556f88>
filename = r'Results\CSV\PUEG1\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_008.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG1\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd071c15c8>
filename = r'Results\CSV\PUEG1\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG1\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd0728e508>
filename = r'Results\CSV\PUEG1\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG1\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd1dfa6948>
filename = r'Results\CSV\PUEG1\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG1\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG1\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd2207e048>
filename = r'Results\CSV\PUEG1\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd22025688>
filename = r'Results\CSV\PUEG1\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd071037c8>
filename = r'Results\CSV\PUEG1\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd0238e188>
filename = r'Results\CSV\PUEG1\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd01ccf048>
filename = r'Results\CSV\PUEG1\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd20925488>
filename = r'Results\CSV\PUEG1\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd030e0388>
filename = r'Results\CSV\PUEG2\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_007.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG2\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd01d23948>
filename = r'Results\CSV\PUEG2\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG2\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd06778648>
filename = r'Results\CSV\PUEG2\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG2\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd01c93508>
filename = r'Results\CSV\PUEG2\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_010.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG2\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd023e0988>
filename = r'Results\CSV\PUEG2\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_008.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG2\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd01d2fc08>
filename = r'Results\CSV\PUEG2\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG2\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG2\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd01d00708>
filename = r'Results\CSV\PUEG2\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd09b846c8>
filename = r'Results\CSV\PUEG2\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd0709d0c8>
filename = r'Results\CSV\PUEG2\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd01ce1088>
filename = r'Results\CSV\PUEG2\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd07071ac8>
filename = r'Results\CSV\PUEG2\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd01c85bc8>
filename = r'Results\CSV\PUEG2\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd09a706c8>
filename = r'Results\CSV\PUEG4\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_013.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG4\PV_Limite_001.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd07002c88>
filename = r'Results\CSV\PUEG4\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_004.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
ax.annotate("Início do steady-state",
xy=(475, 0.175), xycoords='data',
xytext=(0, 0.35), textcoords='data',
size=18,
arrowprops=dict(arrowstyle = '->',
connectionstyle="arc3",
facecolor = 'k',
edgecolor = 'k'
),
)
ax.axvline(600, ls='--', color='k')
<matplotlib.lines.Line2D at 0x1678136db08>
filename = r'Results\CSV\PUEG4\PV_Limite_002.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd09ae2708>
filename = r'Results\CSV\PUEG4\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_011.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG4\PV_Limite_003.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd09b830c8>
filename = r'Results\CSV\PUEG4\PV_Limite_004.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd021d9448>
filename = r'Results\CSV\PUEG4\PV_Limite_005.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd022a6148>
filename = r'Results\CSV\PUEG4\PV_Limite_006.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd09c4fd48>
filename = r'Results\CSV\PUEG4\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_009.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG4\PV_Limite_007.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd02142588>
filename = r'Results\CSV\PUEG4\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_012.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
filename = r'Results\CSV\PUEG4\PV_Limite_008.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd06f56388>
filename = r'Results\CSV\PUEG4\PV_Limite_009.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd06f510c8>
filename = r'Results\CSV\PUEG4\PV_Limite_010.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd06e756c8>
filename = r'Results\CSV\PUEG4\PV_Limite_011.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd09ab0288>
filename = r'Results\CSV\PUEG4\PV_Limite_012.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd20a24148>
filename = r'Results\CSV\PUEG4\PV_Limite_013.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd11e0d8c8>
filename = r'Results\CSV\PUEG4\PV_Limite_014.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
filename = r'Results\CSV\PUEG4\PV_Limite_015.csv'
df2 = pd.read_csv(filename, header = 17, skiprows = [21])
df['Tempo (s)']= df['T'].round(0)
df['Repetição'] = 'A'
df2['Tempo (s)']= df2['T'].round(0)
df2['Repetição'] = 'B'
df['COF (-)'] = df['COF']
df2['COF (-)'] = df2['COF']
df = df.append(df2,ignore_index=True).dropna(axis = 'rows')
plt.figure(figsize=(5, 5))
ax = sns.lineplot(data = df[df['Repetição']!=0], x = 'Tempo (s)', y = 'COF (-)', hue = 'Repetição')
ax.set(ylim = (0, 0.4))
[(0, 0.4)]
df.tail(1615048//4)['COF (-)'].describe()
count 403762.000000 mean 0.144294 std 0.044454 min 0.000000 25% 0.113000 50% 0.145000 75% 0.179000 max 0.273000 Name: COF (-), dtype: float64
filename = r'Results\CSV\PUEG4\PV_Limite_014.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd21f76188>
filename = r'Results\CSV\PUEG4\PV_Limite_015.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd11e04cc8>
filename = r'Results\CSV\PUEG4\PV_Limite_016.csv'
df = pd.read_csv(filename, header = 17, skiprows = [21])
df[(df['T']>705)&(df['T']<706)].plot(kind = 'line', x = 'T', y='COF')
df['T_r']= df['T'].round(0)
sns.relplot(data = df, x = 'T_r', y = 'COF', kind='line')
<seaborn.axisgrid.FacetGrid at 0x1dd209bcc88>